Nonparametric Statistical Downscaling of Precipitation from Global Climate Models

Nyeko-Ogiramoi, Paul; Willems, Patrick; Ngirane-Katashaya, Gaddi; Ntegeka, Victor

doi:10.5772/32910

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…Because the Delta change method only considers the change of quantities, fully describing the changes of certain climate variables such as precipitation is difficult. Therefore, a more sophisticated approach, the WDP method (Liu et al, 2011a;Nyeko-Ogiramoi et al, 2012;Onyutha et al, 2016), was applied to consider the changes in both precipitation amount and frequency. The work flow is summarized in Figure 2 and the detailed steps are described below.…”

Section: Wet Day Perturbation Methodsmentioning

confidence: 99%

Defining spatiotemporal characteristics of climate change trends from downscaled GCMs ensembles: how climate change reacts in Xinjiang, China

Luo

Frankl

Duan

et al. 2018

Intl Journal of Climatology

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The fragile ecosystem, scarce water resources, and limited ecosystem resilience of Xinjiang, China make the region especially vulnerable to climate change. Researchers need reliable analyses of climate change trends to formulate regional mitigation and adaption strategies and to support sustainable development. Therefore, two statistical downscaling methods and the combination of a Mann–Kendall test with Co‐Kriging interpolation were used to investigate the spatiotemporal characteristics of climate change in Xinjiang based on the ensemble of 37 general circulation models (GCMs) in 2021–2060. The reliabilities of single run and ensemble downscaling results of GCMs were evaluated by 69 meteorological stations over the period 1965–2004. The correlation coefficients (CC) with the observations for precipitation and temperature ranged between 0.4–0.8 and 0.9–0.99 in the reference period, respectively. CC improved to 0.87 and was close to 1 after downscaling for precipitation and temperature, respectively. A pronounced increase of ca. 0.27–0.51 °C decade−1 was projected overall, and especially for Representative Concentration Pathway (RCP) 8.5 in northern Xinjiang. In general, the precipitation changed by −1.66 to 6.83% decade−1 while varying seasonally and spatially; a declining tendency emerged in the western regions of Xinjiang during summer. More extreme rainfall events are predicted to occur in summer and autumn months, while warmer extremes would be concentrated in August. The climate in Xinjiang will continue to become warmer and wetter. Nevertheless, Western Xinjiang will experience a warmer and drier climate in summer and autumn. These projections of climate change in the near future are able to provide useful information for the development of potential mitigation measures and adaptation strategies. Multiple circulation mechanisms are also suggested accounting for the changes in precipitation and temperature which will benefit the understanding of the possible drivers of climate variability in this region.

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Section: Wet Day Perturbation Methodsmentioning

confidence: 99%

Defining spatiotemporal characteristics of climate change trends from downscaled GCMs ensembles: how climate change reacts in Xinjiang, China

Luo

Frankl

Duan

et al. 2018

Intl Journal of Climatology

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“…On the other hand, there is only one study that attempted the correction method for rainfall duration bias. Nyeko-Ogiramoi et al (2012) defined the length of consecutive wet days as a wet spell and corrected the mean of the wet spell by extending additional wet days FIG. 2.…”

Section: Introductionmentioning

confidence: 99%

Heavy Rainfall Duration Bias in Dynamical Downscaling and Its Related Synoptic Patterns in Summertime Asian Monsoon

Tamaki

Inatsu

Nguyen-Le

et al. 2018

Journal of Applied Meteorology and Climatology

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Dynamical downscaling (DDS) was conducted over Japan by using a regional atmospheric model with reanalysis data to investigate the rainfall duration bias over Kyushu, Japan, in July and August from 2006 to 2015. The model results showed that DDS had a positive rainfall duration bias over Kyushu and a dry bias over almost all of Kyushu, which were emphasized for extreme rainfall events. Investigated was the rainfall duration bias for heavy rainfall days, accompanied by synoptic-scale forcing, in which daily precipitation exceeded 30 mm day−1 and covered over 20% of the Kyushu area. Heavy rainfall days were sampled from observed rainfall data that were based on rain gauge and radar observations. A set of daily climatic variables of horizontal wind and equivalent potential temperature at 850 hPa and sea level pressure, around southwestern Japan, corresponding to the sampled dates, was selected to conduct a self-organizing map (SOM) and K-means method. The SOM and K-means method objectively classified three synoptic patterns related to heavy rainfall over Kyushu: strong monsoon, weak monsoon, and typhoon patterns. Rainfall duration had a positive bias in western Kyushu for the strong monsoon pattern and a positive bias in southern and east-coast Kyushu for the typhoon pattern, whereas there was little rainfall duration bias in the weak monsoon pattern. The bias for the typhoon pattern was related to rainfall events with a strong rainfall peak. The results suggest that bias correction for rainfall duration would be required for accurately estimating direct runoff in a catchment area in addition to the precipitation amount.

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“…Some further details on the climate models can be found in Appendix A. The GCMs of the CMIP3 and CMIP5 simulations were selected for analyses following their use in previous studies (Onyutha et al 2016;Nyeko-Ogiramoi et al 2012b) for investigation of the impacts of climate change on the rainfall across the LVB.…”

Section: Climate Modelsmentioning

confidence: 99%

How well do climate models reproduce variability in observed rainfall? A case study of the Lake Victoria basin considering CMIP3, CMIP5 and CORDEX simulations

Onyutha

Rutkowska

Nyeko-Ogiramoi³

et al. 2018

Stoch Environ Res Risk Assess

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Nonparametric Statistical Downscaling of Precipitation from Global Climate Models

Cited by 6 publications

References 28 publications

Defining spatiotemporal characteristics of climate change trends from downscaled GCMs ensembles: how climate change reacts in Xinjiang, China

Defining spatiotemporal characteristics of climate change trends from downscaled GCMs ensembles: how climate change reacts in Xinjiang, China

Heavy Rainfall Duration Bias in Dynamical Downscaling and Its Related Synoptic Patterns in Summertime Asian Monsoon

How well do climate models reproduce variability in observed rainfall? A case study of the Lake Victoria basin considering CMIP3, CMIP5 and CORDEX simulations

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